10x Xenium
Human skin of body
GSM9079610
silver Interactive viewer No linked publication
print(sdata)
SpatialData object
├── Images
│ └── 'morphology_mip': DataTree[cyx] (1, 13808, 14352), (1, 6904, 7176), (1, 3452, 3588), (1, 1726, 1794), (1, 863, 897)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (12383, 13233), (6191, 6616), (3095, 3308), (1547, 1654), (773, 827)
│ └── 'nucleus_labels': DataTree[yx] (12337, 12898), (6168, 6449), (3084, 3224), (1542, 1612), (771, 806)
├── Points
│ └── 'transcripts': DataFrame with shape: (1407106, 11) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (9960, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (9960, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (10038, 2) (2D shapes)
└── Tables
└── 'table': AnnData (9960, 100)
with coordinate systems:
▸ 'global', with elements:
morphology_mip (Images), cell_labels (Labels), nucleus_labels (Labels), transcripts (Points), cell_boundaries (Shapes), cell_circles (Shapes), nucleus_boundaries (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("9SxZ5tvxQGNA1yjE") # latest version
sdata = artifact.load() # cache, then load into memory
group = artifact.open() # stream without downloading
path = artifact.cache() # sync into the local cache, returns the path Load from the CLI
# one-shot: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/9SxZ5tvxQGNA1yjE
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid 9SxZ5tvxQGNA1yjE Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["9SxZ5tvxQGNA1yjE0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openMetadata
- Technology
- 10x Xenium
- Organism
- human
- Tissue
- skin of body
- Modality
- RNA
- Observations
- 9,960
- Transcripts
- 1,407,106
- Tier
- silver
- Size
- 231 MB
- Sample ID
- GSM9079610
- License
- unknown
- Published
- Dec 3, 2025
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB